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IEEE Transactions on Signal Processing

Secure Communications for Dual-Polarized MIMO Systems

Shiqi Gong, Chengwen Xing, Sheng Chen, Zesong Fei

Published May 18, 2017• 36 citations
Publisher

Abstract

To enhance secure communications, we deploy the dual-polarized antenna arrays at communication nodes of the multi-input multioutput (MIMO) system, where the base station communicates with multiple legitimate users in the presence of an eavesdropper. We also adopt the dual-structured precoding in which a preprocessing matrix based on the polarized array spatial correlation and a linear precoding based on the instantaneous channel state information (CSI) are concatenated. We design this dual-structured multiuser linear precoding under three cases. In the first case, given perfect global CSI, the secrecy rate optimization problem is formulated and transformed into the weighted minimum mean square error (MSE) problem, which can be effectively solved by the block coordinate decent method. In the second case, where the eavesdropper's CSI is unavailable, an artificial noise is generated to confuse the eavesdropper by minimizing the information transmit power subject to a preset MSE threshold for the recovered confidential signals, which can be solved by an efficient iterative algorithm. In the third case of imperfect global CSI, the robust optimization for secure communications is performed by minimizing the largest received MSE among the users subject to the total transmit power constraint, which can be reformulated into a biconvex semidefinite programming problem and solved by an efficient alternating convex optimization. Simulation results are included to demonstrate the excellent performance of our proposed designs over the conventional single-polarized array-based designs, in terms of achievable secrecy rate, minimum transmit power, and the MSE of recovered confidential signals.

DOI
10.1109/tsp.2017.2706180

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To enhance secure communications, we deploy the dual-polarized antenna arrays at communication nodes of the multi-input multioutput (MIMO) system, where the base station communicates with multiple legitimate users in the presence of an eavesdropper. We also adopt the dual-structured precoding in which a preprocessing matrix based on the polarized array spatial correlation and a linear precoding based on the instantaneous channel state information (CSI) are concatenated. We design this dual-structured multiuser linear precoding under three cases. In the first case, given perfect global CSI, the secrecy rate optimization problem is formulated and transformed into the weighted minimum mean square error (MSE) problem, which can be effectively solved by the block coordinate decent method. In the second case, where the eavesdropper's CSI is unavailable, an artificial noise is generated to confuse the eavesdropper by minimizing the information transmit power subject to a preset MSE threshold for the recovered confidential signals, which can be solved by an efficient iterative algorithm. In the third case of imperfect global CSI, the robust optimization for secure communications is performed by minimizing the largest received MSE among the users subject to the total transmit power constraint, which can be reformulated into a biconvex semidefinite programming problem and solved by an efficient alternating convex optimization. Simulation results are included to demonstrate the excellent performance of our proposed designs over the conventional single-polarized array-based designs, in terms of achievable secrecy rate, minimum transmit power, and the MSE of recovered confidential signals.
This paper investigates secure beamforming design for simultaneous proactive eavesdropping and communication in a multiuser multi-antenna system, where a full-duplex base station (FD-BS) serves multiple legitimate users, monitors a suspicious link, and suppresses multiple eavesdroppers. The proposed design is formulated as maximizing the weighted sum secrecy rate (WSSR) of legitimate users, subject to a total transmit-power requirement and a proactive eavesdropping constraint. The initial problem is hard to solve due to the high non-convexity of the objective function and the proactive eavesdropping constraint. By introducing three auxiliary variables, the original WSSR maximization problem is equivalently reformulated as a weighted minimum mean square error (WMMSE) minimization problem. The reformulated WMMSE minimization problem remains non-convex, where a block coordinate descent (BCD) algorithm based on first-order Taylor approximation is proposed to solve it iteratively. Aiming to reduce the computational complexity of the proposed method, a low complexity zero-forcing beamforming algorithm is designed. Simulation results demonstrate that the proposed algorithms can achieve superior trade-offs among communication efficiency, secrecy enhancement, and surveillance performance than conventional methods.
This paper studies masked beamforming schemes for secure communication in broadcast multiple-input multiple-output (MIMO) systems with a passive multiple-antenna eavesdropper. Assuming no information about the eavesdropper is available at the transmitter, we aim to maximize the transmit power of the artificial noise while meeting mean square error (MSE) constraints at the legitimate receivers and the total power constraint at the transmitter. Based on imperfect channel state information (CSI) of the legitimate receivers at the transmitter, we present a worst-case robust masked beamforming algorithm. By exploiting alternating iterative optimization, the proposed algorithm recasts the non-convex optimization problem as two semidefinite program (SDP) based subproblems, which are solvable with interior-point methods. Simulation results are provided to illustrate the secrecy performance of the proposed algorithm.
This paper considers a movable antenna (MA)-aided secure multiple-input multiple-output (MIMO) communication system consisting of a base station (BS), a legitimate information receiver (IR) and an eavesdropper (Eve), where the BS is equipped with MAs to enhance the system’s physical layer security (PLS). Specifically, we aim to maximize the secrecy rate (SR) by jointly optimizing the transmit precoding (TPC) matrix, the artificial noise (AN) covariance matrix and the MAs’ positions under the constraints of the maximum transmit power and the minimum spacing between MAs. To solve this non-convex problem with highly coupled optimization variables, the block coordinate descent (BCD) method is applied to alternately update the variables. Specifically, we first reformulate the SR into a tractable form, and derive the optimal TPC matrix and the AN covariance matrix with fixed MAs’ positions by applying the Lagrangian multiplier method in semi-closed forms. Then, the majorization-minimization (MM) algorithm is employed to iteratively optimize each MA’s position while keeping others fixed. We also extend this work to the more general multicast scenario. Finally, simulation results are provided to demonstrate the effectiveness of the proposed algorithms and the significant advantages of the MAs over conventional fixed position antennas (FPAs) in enhancing system’s security.
In this paper, we consider a multiuser multiple-input multiple-output (MIMO) downlink communication system with simultaneous wireless information and power transfer (SWIPT). In particular, we focus on a realistic and efficient multi-receiver multi-eavesdropper MIMO SWIPT system, in which the channel state information (CSI) of each legitimate receiver and energy receiver (i.e., potential eavesdropper) is partially known to the transmitter. Based on this, we propose a robust artificial noise (AN)-aided secure transmission scheme for the system, where the channel uncertainties are modeled by the worst-case model. In the proposed scheme, we aim to maximize the worst-case achievable secrecy rate under the transmit power constraint and the energy harvesting (EH) constraint, by jointly optimizing the transmit precoding matrix and the AN covariance matrix. We utilize the S-Procedure and Taylor series approximation to transform the non-convex problem. Then, we apply the interior point method to tackle the transformed convex problem, obtaining the approximate optimal matrices and the corresponding maximum worst-case secrecy rate. Simulation results show that our proposed scheme achieves significant performance improvements in terms of convergence and the worst-case achievable secrecy rate.
We study the design of linear precoders for secure transmission in the two-user multiple-input single-output (MISO) broadcast channel with confidential messages (BC-CM). The transmitter has multiple antennas, and each user has a single receive antenna. Two independent messages are simultaneously transmitted, one intended for each user, and each message should be kept confidential from the other user. Assuming real-valued transmitted signals, we design the linear precoders subject to total and per-antenna average power constraints, and also subject to amplitude constraints. In both cases, we tackle the design problem via weighted secrecy sum rate maximization. The resulting problem, however, involves a fractional objective, making it nonconvex and difficult to solve. Nevertheless, we show that this difficult problem can be transformed into a more tractable problem, for which a solution can be obtained by an iterative search algorithm. In addition, we characterize a condition under which the obtained solution is guaranteed to be optimal. Furthermore, we show that the problem formulation and solution approach can be easily extended to handle the robust version of the design problem with uncertain channel information. We provide numerical examples to demonstrate the performance of the proposed precoder in terms of the achievable secrecy rate regions subject to the aforementioned constraints. We also demonstrate the performance of the robust precoder under different channel uncertainty levels.
This paper studies secure wireless transmission from a multi-antenna transmitter to a single-antenna intended receiver overheard by multiple eavesdroppers with considering the imperfect channel state information (CSI) of wiretap channel.To enhance security of communication link, the artificial noise (AN) is generated at transmitter.We first design the robust joint optimal beamforming of secret signal and AN to minimize transmit power with constraints of security quality of service (QoS), i.e., minimum allowable signal-to-interference-and-noise ratio (SINR) at receiver and maximum tolerable SINR at eavesdroppers.The formulated design problem is shown to be nonconvex and we transfer it into linear matrix inequalities (LMIs).The semidefinite relaxation (SDR) technique is used and the approximated method is proved to solve the original problem exactly.To verify the robustness and tightness of proposed beamforming, we also provide a method to calculate the worst-case SINR at eavesdroppers for a designed transmit scheme using semidefinite programming (SDP).Additionally, the secrecy rate maximization is explored for fixed total transmit power.To tackle the nonconvexity of original formulation, we develop an iterative approach employing sequential parametric convex approximation (SPCA).The simulation results illustrate that the proposed robust transmit schemes can effectively improve the transmit performance.